In order to inform model building, we first observed simple visualizations of our four predictors (percentage of ESL speakers, percentage of non-White residents, rent burden, and population density) over a choropleth of eviction rates in Brooklyn by census tract in 2010.
Results were as follows:
Census tracts with a higher percentage of ESL speakers appear to have lower eviction rates. English language nativity appears to be geographically clustered.
Census tracts with a higher percentage of non-White residents appear to have higher eviction rates. Racial composition of census tracts appears to be geographically clustered.
The relationship between eviction rates and rent burden were not immediately obvious. However, census tracts with high rent burdens appeared to be geographically clustered.
A weak relationship seems to exist between population density and eviction rates, with eviction rates lower in more densely populated census tracts. Census tracts with high rent burdens appeared to be weakly geographically clustered.
Based on 2010 data on hypothesized predictors of eviction rates in Brooklyn, we identified clear associations between the percentage of non-White residents and evictions rates in a given census tract.
Gloria Hu, Naama Kipperman, Will Simmons, Frances Williams
Visualizations and analyses performed using R (v3.6.1) and RStudio (v1.2.1335).
Additional interactivity added using plotly (v4.9.0) and Shiny (v1.3.2).
2019